<HashMap><database>BioModels</database><file_versions><headers><Content-Type>application/xml</Content-Type></headers><body><files><Txt>https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000111?filename=curation_notes.txt</Txt><Pdf>https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000111?filename=BIOMD0000000111.pdf</Pdf><Owl>https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000111?filename=BIOMD0000000111-biopax3.owl</Owl><Owl>https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000111?filename=BIOMD0000000111-biopax2.owl</Owl><Svg>https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000111?filename=BIOMD0000000111.svg</Svg><Xml>https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000111?filename=BIOMD0000000111_url.xml</Xml><Xml>https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000111?filename=manifest.xml</Xml><Other>https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000111?filename=curation_image.png</Other><Other>https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000111?filename=BIOMD0000000111_url.sedml</Other><Other>https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000111?filename=BIOMD0000000111.png</Other><Other>https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000111?filename=BIOMD0000000111.m</Other><Other>https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000111?filename=metadata.rdf</Other><Other>https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000111?filename=BIOMD0000000111-octave.m</Other><Other>https://www.ebi.ac.uk/biomodels/model/download/BIOMD0000000111?filename=BIOMD0000000111-matlab.m</Other></files><type>primary</type></body><statusCodeValue>200</statusCodeValue><statusCode>OK</statusCode></file_versions><scores/><additional><submitter>Harish Dharuri</submitter><curationStatus>Manually curated</curationStatus><modellingApproach>ordinary differential equation model</modellingApproach><levelVersion>L2V4</levelVersion><full_dataset_link>https://www.ebi.ac.uk/biomodels/BIOMD0000000111</full_dataset_link><publication_pubmed>12779461</publication_pubmed><isPrivate>false</isPrivate><repository>BioModels</repository><modelFormat>SBML</modelFormat><omics_type>Models</omics_type><tokenised_name>Novak2001 FissionYeast CellCycle</tokenised_name><publication_year>2001</publication_year><submissionId>MODEL6488296959</submissionId><publication_authors>Béla Novák, Zsuzsa Pataki, Andrea Ciliberto, Tyson JJ</publication_authors><first_author>Béla Novák</first_author><publication>12779461,
                            Much is known about the genes and proteins controlling the cell cycle of fission yeast. Can these molecular components be spun together into a consistent mechanism that accounts for the observed behavior of growth and division in fission yeast cells? To answer this question, we propose a mechanism for the control system, convert it into a set of 14 differential and algebraic equations, study these equations by numerical simulation and bifurcation theory, and compare our results to the physiology of wild-type and mutant cells. In wild-type cells, progress through the cell cycle (G1-->S-->G2-->M) is related to cyclic progression around a hysteresis loop, driven by cell growth and chromosome alignment on the metaphase plate. However, the control system operates much differently in double-mutant cells, wee1(-) cdc25Delta, which are defective in progress through the latter half of the cell cycle (G2 and M phases). These cells exhibit "quantized" cycles (interdivision times clustering around 90, 160, and 230 min). We show that these quantized cycles are associated with a supercritical Hopf bifurcation in the mechanism, when the wee1 and cdc25 genes are disabled. (c) 2001 American Institute of Physics.. 1, 11.
                            Department of Agricultural Chemical Technology, Budapest University of Technology and Economics, Szt Gellert ter 4, 1111 Budapest, Hungary.</publication><submitter_mail>hdharuri@cds.caltech.edu</submitter_mail><submitter_affiliation>California Institute of Technology</submitter_affiliation><publicationId>BIOMD0000000111</publicationId><pubmed_abstract>Much is known about the genes and proteins controlling the cell cycle of fission yeast. Can these molecular components be spun together into a consistent mechanism that accounts for the observed behavior of growth and division in fission yeast cells? To answer this question, we propose a mechanism for the control system, convert it into a set of 14 differential and algebraic equations, study these equations by numerical simulation and bifurcation theory, and compare our results to the physiology of wild-type and mutant cells. In wild-type cells, progress through the cell cycle (G1-->S-->G2-->M) is related to cyclic progression around a hysteresis loop, driven by cell growth and chromosome alignment on the metaphase plate. However, the control system operates much differently in double-mutant cells, wee1(-) cdc25Delta, which are defective in progress through the latter half of the cell cycle (G2 and M phases). These cells exhibit "quantized" cycles (interdivision times clustering around 90, 160, and 230 min). We show that these quantized cycles are associated with a supercritical Hopf bifurcation in the mechanism, when the wee1 and cdc25 genes are disabled. (c) 2001 American Institute of Physics.</pubmed_abstract><pubmed_title>Mathematical model of the cell division cycle of fission yeast.</pubmed_title><pubmed_authors>Novak Bela B, Pataki Zsuzsa Z, Ciliberto Andrea A, Tyson John J. JJ</pubmed_authors></additional><is_claimable>false</is_claimable><name>Novak2001_FissionYeast_CellCycle</name><description>
      
        The model reproduces the time evolution of several species as depicted in Fig 4 of the paper. Events have been used to reset  cell mass when the value of M-phase promoting factor (MPF) decreases through 0.1. The model was successfully tested on Cell Designer.
            
            To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to      CC0 Public Domain Dedication
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            In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not.
            
            To cite BioModels Database, please use:      Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.
                
            
      
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